Data Science, Post-Baccalaureate Certificate

Student Learning Outcomes

• Perform quantitative data analysis using appropriate statistical methods and tools (SAS) to aid business decisions and reduce the risks and optimize solutions.
• Explore data to understand relationships among variables and harness / mine very large data sets to make business decisions using machine learning techniques.
• Apply data visualization best practices to communicate visual insights through charts, dashboards and communicate data-driven stories.
• Integrate, apply and implement the concepts, techniques and tools of data analytics learnt in the MS DSA Program using capstone projects with real-world datasets.
• Identify and explain knowledge in data science, big data, and technology used for processing big data and data science methods.
• Formulate and solve data science and big data problems using appropriate data management and analysis skills.
• Identify and apply the technology necessary to aid in solving real-world problems.
• Effectively use technology to solve data science problems.
• Be literate in the language of data science and in data analysis skills for data science and big data.

Curriculum Requirements

Required Advanced

• MATH 6100 - Data Preparation and Cleaning Credit Hours: 3
• MATH 6200 - Data Visualization Credit Hours: 3
• MATH 6300 - Big Data Tools Credit Hours: 3
• MATH 6400 - Big Data Analytics Credit Hours: 3
• MATH 6900 - Data Science and Analytics Capstone I Credit Hours: 3

Total Number of Credits to Complete the Program: 15